enquire-mcp

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<a href="https://github.com/oomkapwn/enquire-mcp"><img src="./assets/social-preview.png" alt="enquire-mcp — the most advanced Obsidian MCP. Long-term memory for AI agents. Built on your Obsidian vault. Open-source, MCP-native, vendor-neutral. Hybrid retrieval, BGE reranker, HNSW, PDFs with OCR. For Claude Code, Claude Desktop, Cursor, ChatGPT, Codex, OpenClaw." width="100%"></a>

# enquire-mcp

<sub>**English** · [中文](./README.zh.md) · [Español](./README.es.md) · [हिन्दी](./README.hi.md) · [العربية](./README.ar.md) · [Русский](./README.ru.md) · [Português](./README.pt.md) · [Français](./README.fr.md) · [日本語](./README.ja.md) · [한국어](./README.ko.md) · [Deutsch](./README.de.md)</sub>

<sub>**TL;DR for AI agents** — MCP server exposing a local Obsidian markdown vault to Claude Code, Claude Desktop, Cursor, ChatGPT, Codex, and OpenClaw as persistent searchable memory. Hybrid retrieval (BM25 + ML embeddings + BGE reranker, RRF-fused), HNSW + int8 quantization, agentic RAG (HyDE + sub-question), GraphRAG-light, PDFs + OCR, standalone Bases. Vendor-neutral, MIT, zero cloud calls during serve. Install: `npm i -g @oomkapwn/enquire-mcp`. Docs: [llms.txt](https://github.com/oomkapwn/enquire-mcp/blob/main/llms.txt) · [AGENTS.md](https://github.com/oomkapwn/enquire-mcp/blob/main/AGENTS.md) · [API](https://oomkapwn.github.io/enquire-mcp/).</sub>

### The most advanced Obsidian MCP. Long-term memory for AI agents.

**Stop re-explaining context to Claude, Cursor, ChatGPT, Codex, OpenClaw every session. Your Obsidian notes become shared, searchable memory across every MCP-compatible agent — your knowledge, every model, forever yours.**

*Measured: the BGE cross-encoder reranker adds **+15.5 NDCG@10 / +24.7 MRR** over plain hybrid on a [reproducible 60-query ablation](./docs/benchmarks.md) — the full modern IR stack, recalling the markdown **you** wrote (cited, editable), never a cloud paraphrase.*

[![CI](https://github.com/oomkapwn/enquire-mcp/actions/workflows/ci.yml/badge.svg)](https://github.com/oomkapwn/enquire-mcp/actions/workflows/ci.yml)
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[![tests](https://img.shields.io/badge/tests-1594%20passing-brightgreen.svg)](#️-trust)
[![stable](https://img.shields.io/badge/v3.11.x-stable-brightgreen.svg)](./STABILITY.md)
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**[⚡ 30-second install](#-quick-start) · [🧠 Use cases](#-use-cases) · [📊 Benchmarks](./docs/benchmarks.md) · [📖 API reference](https://oomkapwn.github.io/enquire-mcp/) · [💬 Compare alternatives](./docs/COMPARISON.md)**

**Claude Code — one line:**

```bash
claude mcp add obsidian -- npx -y @oomkapwn/enquire-mcp serve --vault ~/Documents/Obsidian\ Vault
```

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---

## The problem

Every AI session starts from zero. You re-explain your project, your design decisions, the conclusions of last week's research. Vendor "memory" features ([Claude Memory](https://www.anthropic.com/news/memory-and-tool-use), [ChatGPT Memory](https://openai.com/index/memory-and-new-controls-for-chatgpt/), Cursor memory) lock your knowledge into one provider's cloud — and forget it again when you switch tools. **Your knowledge keeps starting over.**

## The solution

Your Obsidian vault becomes **persistent, queryable long-term memory** for any MCP-compatible agent. One install — your knowledge is instantly accessible from Claude Code, Claude Desktop, Cursor, ChatGPT custom GPT, Codex, OpenClaw, and every other MCP client. Plain markdown files **you own**, indexed locally, searched with the full modern IR stack, recalled across every session and every model.

**Grounded, not extracted.** Conversation-memory tools (mem0, Zep, Supermemory, Memobase) *extract* facts from your chat logs into a separate store you can't read. enquire-mcp is the inverse: it's **grounded in the knowledge you already wrote** — your own `.md` notes, verbatim, with citations — so recall is auditable, editable in any editor, and never a lossy summary of a chat you half-remember. And unlike server-side ***fleet*-memory** platforms — multi-tenant cloud stores that paraphrase agent traffic into a shared database — enquire is **single-user and local-first**: one vault you own outright and can read, edit, and delete yourself, with zero cloud calls during serve. (That "extracted" critique is specific to the chat-memory cohort — not to knowledge-graph / ETL tools like cognee, nor to personal-search peers like Khoj.)

**Grounded — and freshness-aware.** Recalling a fact is half the problem; knowing whether it's still *true* is the other half. The [Memora benchmark](https://arxiv.org/abs/2604.20006) (Apr 2026) showed memory systems systematically fail at stale-fact reuse — recalling a year-old note as if it were written today. Because enquire's memory *is* your real markdown files, every search hit carries `age_days` + a `stale` flag derived from the note's live last-modified time, and you can opt into recency-weighted ranking (`--recency-weight`) so fresher notes surface first. Your knowledge, freshness-aware — not a timeless blob.

> **What makes enquire-mcp different**:
> 1. **Vendor-neutral.** Your memory lives in `.md` files. Switch from Claude to Cursor — your memory comes with you.
> 2. **Best-in-class retrieval.** Hybrid BM25 + multilingual embeddings + BGE cross-encoder reranker fused via RRF, scaled with HNSW + int8 quantization. The same IR stack a search startup would build — open-sourced, in one binary.
> 3. **Zero cloud calls during serve.** The embedding model runs **on your machine** and indexes the markdown **you** wrote — that's why it's a one-time local download (~110 MB), not a cloud API key. Grounded + private isn't free, and we don't pretend it is: your vault content never leaves your machine, air-gap-safe by default ([enforced](./SECURITY.md), not aspirational).
> 4. **Freshness-aware recall.** Every hit reports how old the note is; opt-in recency re-ranking lets an agent prefer fresh knowledge and flag stale facts for re-verification — the forgetting-aware frontier, built on the `mtime` your files already have.

**46 tools · 19 MCP prompts · 1594 unit tests · 50+ languages · v3.11.x stable · semver-bound · MIT · npm build provenance (SLSA L2).**

---

## 🏆 Why it's the best

**Six features no other Obsidian-MCP has at all** (GraphRAG-light, standalone `.base` execution, HyDE, int8 quantization, late-chunking, built-in eval harness). **Plus the entire modern IR stack** (BM25 + ML embeddings + cross-encoder reranking + HNSW) that competitors ship at most one or two of. Side-by-side:

| Capability | enquire-mcp | Smart Connections | Other Obsidian-MCPs |
|---|:---:|:---:|:---:|
| Hybrid retrieval (BM25 + TF-IDF + ML embeddings, RRF-fused) | ✅ | ❌ | ❌ |
| **Cross-encoder reranking** (BGE, +15.5 NDCG@10 measured) | ✅ | ❌ | ❌ |
| **HNSW vector index** (sub-10ms top-K, persisted) | ✅ | ❌ | ❌ |
| **int8 vector quantization** (~4× smaller embed-db) | ✅ | ❌ | ❌ |
| **Late-chunking** context-windowed embeddings | ✅ | ❌ | ❌ |
| **PDFs blended into hybrid search** (`[page: N]` citations) | ✅ | ❌ | ❌ |
| **OCR for scanned PDFs** (Tesseract.js, multilingual) | ✅ | ❌ | ❌ |
| **Wikilink graph-boost** retrieval signal | ✅ | ❌ | ❌ |
| **Multilingual semantic search** (50+ languages, on-device) | ✅ | 💰 paid | ❌ |
| **Built-in retrieval-quality eval harness** (NDCG, Recall, MRR, A/B matrix) | ✅ | ❌ | ❌ |
| **Remote MCP** over HTTP + bearer auth + stateful sessions | ✅ | ❌ | partial |
| **Per-signal observability** per hit | ✅ | ❌ | ❌ |
| **MCP-native** (Claude · Cursor · ChatGPT · Codex · OpenClaw · any client) | ✅ | ❌ Obsidian-only | varies |
| **Privacy filter** verified at every search + write path | ✅ | n/a | ❌ |
| **46 production tools** (34 always-on read tools + 4 opt-in + 7 gated writes + 1 feedback tool) | ✅ | n/a | varies |
| **GraphRAG-light** (wikilink community detection via Louvain modularity) | ✅ **only here** | ❌ | ❌ |
| **Standalone `.base` query execution** (works without Obsidian running) | ✅ **only here** | ❌ | ❌ delegates to Obsidian |
| **HyDE retrieval** (Gao et al 2023) + sub-question decomposition | ✅ **only here** | ❌ | ❌ |
| **1594 unit tests · 9 required + 5 advisory CI gates per PR** | ✅ | n/a | rare |
| **Signed build provenance** (npm + Sigstore, SLSA Build L2) | ✅ | n/a | ❌ |
| **Semver-bound public surface** ([STABILITY.md](./STABILITY.md)) | ✅ | n/a | ❌ |
| Standalone (no Obsidian plugin needed) | ✅ | ❌ requires Obsidian | varies |
| License | MIT, free | proprietary, paid | varies |

<sub>Comparison based on each project's public capabilities as of v3.8.x stable (initial snapshot v3.7.0 / 2026-05-15; refreshed in v3.8.4). Smart Connections is a paid Obsidian plugin (not an MCP server). "Other Obsidian-MCPs" refers to public open-source Obsidian-MCP servers on GitHub at time of writing. Public end-to-end retrieval benchmarks for enquire-mcp are published in <a href="./docs/benchmarks.md"><code>docs/benchmarks.md</code></a> — measured `rerank-bge` delta is +24.7 MRR / +15.5 NDCG@10 over plain hybrid on a 60-query ablation.</sub>

> Strategic claim: enquire-mcp is the open-source backend for [Karpathy-style LLM Wikis](https://gist.github.com/karpathy/442a6bf555914893e9891c11519de94f) on top of your existing Obsidian vault. Knowledge that compounds, traceable to sources.

---

## ⚡ Quick start

```bash
npm install -g @oomkapwn/enquire-mcp
enquire-mcp serve --vault ~/Documents/Obsidian\ Vault
```

Drop into any MCP client:

```json
{
  "mcpSer